用 GPT-Live-1 构建应用?给它们配一副合适的嗓音。 以下是用提示词塑造音色,或从全新国际预设音色中选择的方法:
全部 AI 动态
OpenAI Developers@OpenAIDevsAI 评分2222
Sam Altman@samaAI 评分1515
Sam Altman@samaAI 评分3838引用Nick@nickcammaratainterpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works https://already-clean.goodfire.com/
Google DeepMind@GoogleDeepMind精选AI 评分7878引用Maxence Faldor@maxencefaldorFour Gemini 4 Argon agents, one shared Minecraft world, one goal: defeat the Ender Dragon. 27 hours and 2,783 self-written programs later, the dragon fell. https://x.com/i/article/2111007444981645312
推荐理由:四个 Gemini 4 Argon 智能体在共享沙盒中自行分工、写码与调试,展示了多智能体协作完成长程任务的一种路径。
Turing Post (Ksenia Se)@TheTuringPostAI 评分5555普林斯顿大学与宾夕法尼亚大学提出 Recurrent Looped Transformer(RLT),让 Transformer 携带一个运行状态并在每个 token 后更新它。
Hugging Face@huggingfaceAI 评分5555Hugging Face 以直播形式发布一款新的开放权重模型,并给出直播链接 https://x.com/i/broadcasts/1DxleVaPLagKL。原文未披露模型名称、参数规模或能力细节。
Hugging Face@huggingface精选AI 评分7878引用Reflection@reflection_aiBeam is now available across platforms, with open weights under the Apache 2.0 license - in collaboration with an ecosystem of 40+ partners. We're releasing: - Weights, tokenizer, and reference implementation - BF16, FP8 and NVFP4 weights and a DFlash2 drafter - The open source harness we built and trained Beam on: Mirror CLI Weights and model card on Hugging Face: https://huggingface.co/reflection
推荐理由:Reflection 公开 Beam 的权重、量化版本与训练工具 Mirror CLI,可据此了解其开放程度与复现路径。
Google DeepMind@GoogleDeepMindAI 评分2222
AK@_akhaliqAI 评分3838混合推理智能体 论文:https://huggingface.co/papers/2610.18861

Latent SpaceAI 评分6262 Goodfire 提出神经网络已足够清晰,可解释性争论再起
Goodfire 的 Nick Cammarata 发布文章提出“神经网络已经足够清晰”,认为许多被视为多义性和叠加的案例经进一步智能体分析后可以解读,并称 2023 年 OpenAI 自动化可解释性工作只找到约 2% 可读神经元,很多著名多义性案例被误读。
MiniMax (official)@MiniMax_AIAI 评分1818引用Matt White@matthew_d_whiteOpen Source AI Week started with a handful of events and a community bringing people together. Now in its third year, we have 65 events on the calendar—and we kick off tomorrow! Explore the lineup: https://opensourceaiweek.com/ Four highlights: 🎉 Tomorrow, Oct 16: Official Kickoff Party, hosted by Hugging Face https://luma.com/OpenTogether 🛠️ Saturday–Sunday, Oct 17–18: ExecuTorch Hackathon https://luma.com/executorch-hackathon 🎙️ Monday night, Oct 19: Open Weight Debates https://luma.com/592fcwx2 🏆 Next Friday, Oct 23: Open Source AI Awards Night, capping off the week https://luma.com/7ebvz0oq The Open Intelligence Foundation (@open_intel_fdn) is proud to be this year’s organizer, alongside a dedicated volunteer team and 32 backing organizations. Our commitment: • Official events will always be free and community-run. • We’ll work to bring the community together to plan diverse, high-value events at no cost, accessible to everyone. • We will never decline an event because it overlaps with one of ours. That goes against the spirit of open source and community. A shared calendar should create more opportunities to participate, collaborate, and learn. I’m proud to have been involved this year and grateful to everyone who made it happen. Thank you to our sponsors: @GoogleDeepMind, @Azure, @arcee_ai, @SemiAnalysis_, and @NEARProtocol Foundation. And our event hosts: @github, @fdotinc, @hackersquadio, @OSS4AI, @Qualcomm, @AIatMeta, @huggingface , @allen_ai, @MiniMax_AI, @UnslothAI, @PrimeIntellect, @NousResearch, @openclaw Foundation, @vllm_project, @lmsysorg, @inferact, @radixark and @anyscalecompute. Find the events that interest you and join us! https://opensourceaiweek.com/ #OpenSourceAIWeek #OpenIntelligence
Turing Post (Ksenia Se)@TheTuringPostAI 评分2222
Turing Post (Ksenia Se)@TheTuringPostAI 评分2525OpenAI NewsAI 评分2020 Benefit Street Partners 用 Codex 更快回答客户问题
Benefit Street Partners 的 Anant Kumar 借助 Codex 进行代码审查并加快后续跟进,从而更快回答客户问题。他用 Codex 构建了用于比较贷款估值和分析信贷协议的工具。
OpenAI NewsAI 评分3535 Stack Overflow for Agents 借 ChatGPT 插件实现注册量三倍增长
Stack Overflow for Agents 借助 ChatGPT 插件将智能体创建量最高提升至 10 倍,注册量增长两倍。两名工程师用 Codex 在数周内完成了该产品的开发与上线。
Mira Murati@miramuratiAI 评分2222今年最棒的部分之一,无论是在 Thinky 内部还是外部,就是看着人们追随自己的想法,一路走到他们自己拥有的权重之中。
引用Thinking Machines@thinkymachinesTinker lets customers turn their expertise into cutting-edge models that they own. One year after launch, we look back at what we’ve shipped and what our users are building. https://thinkingmachines.ai/news/one-year-of-tinker/
OpenAI Developers@OpenAIDevsAI 评分2222你可以直接用 Codex 动手做东西 我们做了一个网站,供你浏览社区里的硬件项目,也可以分享你自己的项目。

Anthropic@AnthropicAIAI 评分4040引用Simons Foundation@SimonsFdnHow can the math community forge the best path forward in the AI age? We're committing $15M to workshops and initiatives — plus free AI computing resources for foundation-supported researchers — through new partnerships with @AnthropicAI and @OpenAI: https://bit.ly/4zpfIbW #math #science #AI
OpenAI Developers@OpenAIDevsAI 评分3232
Turing Post (Ksenia Se)@TheTuringPostAI 评分2222上次我们看到 Logan 一次性采访这么多人,结果 4 个人里有 3 个从 Google 离职了。👀
引用Logan Kilpatrick@OfficialLoganKA conversation with Sergey Brin, @joshwoodward, @tulseedoshi, and @melvinjohnsonp about Gemini 4 Argon, how we got here, and the path ahead!
OpenAI News精选AI 评分6060 OpenAI 推出 Rosalind 学术计划,向合格学术实验室提供 GPT-Rosalind 赞助访问
OpenAI 推出 Rosalind 学术计划,为符合条件的学术实验室提供 GPT-Rosalind 及相关工具的赞助访问,用于推进生命科学研究。
推荐理由:OpenAI 面向学术实验室开放 GPT-Rosalind 的赞助访问,读者可据此了解生命科学研究的准入条件。
AK@_akhaliqAI 评分2222从失败到可学习的世界 面向导航智能体的策略条件环境生成 论文:https://huggingface.co/papers/2610.19420

AI at Meta@AIatMeta精选AI 评分8080推荐理由:Meta 公布开源权重模型的具体参数与多模态规格,可据此判断其长程编码与智能体任务的定位。
NVIDIA Blog精选AI 评分6060 NVIDIA 发布 RTX Spark 笔记本并公布本地 AI 性能测试
NVIDIA 发布面向创作者、游戏玩家和 AI 智能体的 Windows PC 产品 RTX Spark,并在全球多地举办发布活动。
推荐理由:原文给出 RTX Spark 的本地 AI 实测完成时间对比,可据此判断笔记本端侧推理的可用性。
Google DeepMindAI 评分5858 Google DeepMind 演示用 Antigravity 智能体平台发现抗菌肽
Google DeepMind 展示生物学家如何用智能体开发平台 Google Antigravity 在 Streptococcus pseudopneumoniae 中寻找并计算验证新型抗菌肽,候选分子已进入湿实验验证阶段。
Microsoft Research精选AI 评分6060 微软研究院发布 Magnetar:基于标准哈希函数的通用零知识证明系统
微软研究院发布零知识虚拟机 Magnetar,可直接证明用 Rust、Go 或 C 编写的程序执行过程,并输出可在约 12 毫秒内验证的简短证明。在 15 个基准程序上,它比同类最快的 zkVM 平均快 10 到 39 倍,在笔记本上每秒可证明 7.2 至 8.7 百万条 RISC-V 指令。
推荐理由:微软研究院梳理十余年零知识证明研究脉络,说明 Magnetar 如何在通用性、速度与密码学假设之间同时取得进展。
Aran Komatsuzaki@arankomatsuzakiAI 评分4040
Turing Post (Ksenia Se)@TheTuringPostAI 评分3838这篇指南讲解 3D Gaussian Splatting(3DGS)如何把拍摄场景转为机器人的空间记忆,并介绍机器人如何检索、更新该记忆,以及从“记住世界”走向“理解物理”所需的条件。
NVIDIA@nvidia精选AI 评分7373引用NVIDIA AI@NVIDIAAIMeet NVIDIA Nemotron 3.5 Super VL Our new open model combines reasoning and tool use with text, image, document, and video understanding for long-running AI agents. 120B total parameters with 12B active 🧵
推荐理由:官方给出新开源多模态模型的总参数与激活参数,读者可据此判断其本地部署与定制空间。
NVIDIA Blog精选AI 评分7878 NVIDIA 扩展 Nemotron 家族,发布 120B 多模态 Super VL 与两款 Bolt 端侧模型
NVIDIA 发布 Nemotron 3.5 Super VL,这是 120B 参数的开源多模态模型,主打智能体任务的速度与准确率,官方称吞吐量最高可达同类模型的 5 倍。
推荐理由:NVIDIA 一次放出 120B 多模态与两款端侧模型,读者可据此判断本地智能体部署的选型空间。
OpenAI@OpenAIAI 评分4040OpenAI 向 Simons Foundation 新计划出资 500 万美元,用于帮助数学家检验、理解并在此基础上推进 AI 产出的结果,包括 OpenAI 近期发布的研究成果。
引用Simons Foundation@SimonsFdnHow can the math community forge the best path forward in the AI age? We're committing $15M to workshops and initiatives — plus free AI computing resources for foundation-supported researchers — through new partnerships with @AnthropicAI and @OpenAI: https://bit.ly/4zpfIbW #math #science #AI
Aran Komatsuzaki@arankomatsuzakiAI 评分4545这个新基准用领域科学家开发的15个开放科学后续问题评估九个前沿智能体,产出135篇研究论文。 大多数论文未通过完整性检查,包括声称的工作与支撑性执行证据之间的不一致。